89 citations · 116 across the 4 of their papers we have counts for
4 papers
Meta-learning autoencoders for few-shot prediction
Tailin Wu, John Peurifoy, Isaac L. Chuang +1
Compared to humans, machine learning models generally require significantly more training examples and fail to extrapolate from experience to solve previously unseen challenges. To…
Nanophotonic Particle Simulation and Inverse Design Using Artificial Neural Networks
John Peurifoy, Yichen Shen, Li Jing +6
We propose a method to use artificial neural networks to approximate light scattering by multilayer nanoparticles. We find the network needs to be trained on only a small sampling…
Gated Orthogonal Recurrent Units: On Learning to Forget
Li Jing, Caglar Gulcehre, John Peurifoy +4
We present a novel recurrent neural network (RNN) based model that combines the remembering ability of unitary RNNs with the ability of gated RNNs to effectively forget redundant/i…
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing, Yichen Shen, Tena Dubček +5
Using unitary (instead of general) matrices in artificial neural networks (ANNs) is a promising way to solve the gradient explosion/vanishing problem, as well as to enable ANNs to…